Abstract:
We assess site-specific surface shortwave radiation forecasts from two high-resolution configurations of the
South African Weather Service numerical weather prediction model, at 4 and 1.5 km. The models exhibit good skill overall
in forecasting surface shortwave radiation, with zero median error for all radiation components. This information is
relevant to support a growing renewable energy sector in South Africa, particularly for photovoltaics. Further model performance
analysis has shown an imbalance between cloud and solar radiation forecasting errors. In addition, cloud overprediction
does not necessarily equate to underestimating solar radiation. Overcast cloud regimes are predicted too often
with an associated positive mean radiation bias, whereas the relative abundance of partly cloudy regimes is underpredicted
by the models with mixed radiation biases. Challenges highlighted by the misrepresentation of partly cloudy regimes in
solar radiation error attribution may be used to inform improvements to the numerical core, namely, the cloud and radiation
schemes.
SIGNIFICANCE STATEMENT : This paper provides the first comprehensive assessment of high-resolution site-specific
NWP forecasts of surface shortwave radiation in South Africa, exploring clouds as the main drivers of prediction biases.
Error attribution analyses of this kind are close to none for this part of the world. Our study contributes to understanding
how cloud and radiation schemes perform over South Africa, representing a step forward in the state of the art. In addition
to the scientific interest, the capabilities developed through this work may benefit the second largest economy of the continent.
In a country where energy security is of critical relevance, the availability of useful and usable weather information is
paramount to support its industry and socioeconomic growth.
